On the feasibility of distributed process mining in healthcare

Roberto Gatta, Mauro Vallati, Jacopo Lenkowicz, Carlotta Masciocchi, Francesco Cellini, Luca Boldrini, Carlos Fernandez Llatas, Vincenzo Valentini, Andrea Damiani

Risultato della ricerca: Contributo in rivistaContributo a convegno


Process mining is gaining significant importance in the healthcare domain, where the quality of services depends on the suitable and efficient execution of processes. A pivotal challenge for the application of process mining in the healthcare domain comes from the growing importance of multi-centric studies, where privacy-preserving techniques are strongly needed. In this paper, building on top of the well-known Alpha algorithm, we introduce a distributed process mining approach, that allows to overcome problems related to privacy and data being spread around. The introduced technique allows to perform process mining without sharing any patients-related information, thus ensuring privacy and maximizing the possibility of cooperation among hospitals.
Lingua originaleEnglish
pagine (da-a)445-452
Numero di pagine8
RivistaLecture Notes in Computer Science
Stato di pubblicazionePubblicato - 2019
Evento19th International Conference on Computational Science, ICCS 2019 - FARO
Durata: 12 giu 201914 giu 2019


  • Distributed learning
  • Healthcare
  • Process mining


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